caret v4.69

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by Max Kuhn

Classification and Regression Training

Misc functions for training and plotting classification and regression models

Functions in caret

Name Description
bagEarth Bagged Earth
dotPlot Create a dotplot of variable importance values
icr.formula Independent Component Regression
knn3 k-Nearest Neighbour Classification
normalize2Reference Quantile Normalize Columns of a Matrix Based on a Reference Distribution
plotClassProbs Plot Predicted Probabilities in Classification Models
print.train Print Method for the train Class
resampleHist Plot the resampling distribution of the model statistics
resampleSummary Summary of resampled performance estimates
segmentationData Cell Body Segmentation
oneSE Selecting tuning Parameters
tecator Fat, Water and Protein Content of Meat Samples
GermanCredit German Credit Data
confusionMatrix Create a confusion matrix
Alternate Affy Gene Expression Summary Methods. Generate Expression Values from Probes
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification Models
summary.bagEarth Summarize a bagged earth or FDA fit
applyProcessing Data Processing on Predictor Variables (Deprecated)
BloodBrain Blood Brain Barrier Data
xyplot.resamples Lattice Functions for Visualizing Resampling Results
knnreg k-Nearest Neighbour Regression
panel.needle Needle Plot Lattice Panel
pcaNNet.default Neural Networks with a Principal Component Step
postResample Calculates performance across resamples
roc Compute the points for an ROC curve
sensitivity Calculate sensitivity, specificity and predictive values
trainControl Control parameters for train
format.bagEarth Format 'bagEarth' objects
classDist Compute and predict the distances to class centroids
createDataPartition Data Splitting functions
caretFuncs Backwards Feature Selection Helper Functions
sbfControl Control Object for Selection By Filtering (SBF)
filterVarImp Calculation of filter-based variable importance
findLinearCombos Determine linear combinations in a matrix
cox2 COX-2 Activity Data
createGrid Tuning Parameter Grid
featurePlot Wrapper for Lattice Plotting of Predictor Variables
findCorrelation Determine highly correlated variables
predict.knn3 Predictions from k-Nearest Neighbors
dotplot.diff.resamples Lattice Functions for Visualizing Resampling Differences
modelLookup Descriptions Of Models Available in train()
preProcess Pre-Processing of Predictors
caret-internal Internal Functions
resamples Collation and Visualization of Resampling Results
histogram.train Lattice functions for plotting resampling results
diff.resamples Inferential Assessments About Model Performance
spatialSign Compute the multivariate spatial sign
nullModel Fit a simple, non-informative model
caretSBF Selection By Filtering (SBF) Helper Functions
as.table.confusionMatrix Save Confusion Table Results
maxDissim Maximum Dissimilarity Sampling
cars Kelly Blue Book resale data for 2005 model year GM cars
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
rfeControl Controlling the Feature Selection Algorithms
pottery Pottery from Pre-Classical Sites in Italy
predict.bagEarth Predicted values based on bagged Earth and FDA models
print.confusionMatrix Print method for confusionMatrix
plot.varImp.train Plotting variable importance measures
rfe Backwards Feature Selection
nearZeroVar Identification of near zero variance predictors
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
normalize.AffyBatch.normalize2Reference Quantile Normalization to a Reference Distribution
predictors List predictors used in the model
oil Fatty acid composition of commercial oils
train Fit Predictive Models over Different Tuning Parameters
varImp Calculation of variable importance for regression and classification models
predict.train Extract predictions and class probabilities from train objects
lattice.rfe Lattice functions for plotting resampling results of recursive feature selection
plot.train Plot Method for the train Class
bag.default A General Framework For Bagging
prcomp.resamples Principal Components Analysis of Resampling Results
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
dhfr Dihydrofolate Reductase Inhibitors Data
aucRoc Compute the area under an ROC curve
sbf Selection By Filtering (SBF)
bagFDA Bagged FDA
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